Eventual consistency is a model used in distributed computing with the goal that all individual accesses to an item will eventually return the same value. Systems on the Semantic Web that are eventually consistent are often referred to as BASE (Basically Available, Soft state, Eventual consistency). Resource Description Framework (RDF) is an example standard for data interchange on the Web. RDF uses Universal Resource Identifiers (URIs) to describe relationships between things as a subject, predicate, and object (referred to as a “triple”). A URI is a string of characters used to identify a resource. One example of a URI is a Uniform Resource Locator (URL), frequently referred to as a “web address.” RDF can be represented as a directed, labeled graph, where nodes represent Web resources and edges between the nodes represent relationships between the resources.
Applications allowing the production of a very large amount of data can benefit from using an RDF dataset. In such cases, the production of very large numbers of URIs must be supported. A dictionary can be used to provide indexes to RDF triples storage to help optimize the persistence of vastly redundant information. The dictionary and index essentially offer three operations: (1) Insert—attribute an index to a RDF node and store its value in the dictionary, (2) Locate—provide the index associated with a RDF node, and (3) Extract—provide, from the dictionary, the value associated with an index. Locate and Extract operations can be costly as the dictionary grows, as they require accessing the latest updates to the dictionary as a whole from distant sites in order to distribute accurate indexes. The Insert operation can be problematic in the context of a decentralized and distributed dictionary, as two different sites may try to insert the same resource simultaneously.